2021
DOI: 10.1002/psp4.12696
|View full text |Cite
|
Sign up to set email alerts
|

Pharmacometrics meets statistics—A synergy for modern drug development

Abstract: Modern drug development problems are very complex and require integration of various scientific fields. Traditionally, statistical methods have been the primary tool for design and analysis of clinical trials. Increasingly, pharmacometric approaches using physiology‐based drug and disease models are applied in this context. In this paper, we show that statistics and pharmacometrics have more in common than what keeps them apart, and collectively, the synergy from these two quantitative disciplines can provide … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
6
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
7
1

Relationship

2
6

Authors

Journals

citations
Cited by 14 publications
(9 citation statements)
references
References 92 publications
0
6
0
Order By: Relevance
“…Finally, we think that the CGM data analysis provides an opportunity for a collaborative effort, integrating clinical, statistical, data science, and pharmacometrics expertise. Such a combination is increasingly viewed as being synergistic in solving complex problems in biomedical research ( 45 , 46 ).…”
Section: Discussionmentioning
confidence: 99%
“…Finally, we think that the CGM data analysis provides an opportunity for a collaborative effort, integrating clinical, statistical, data science, and pharmacometrics expertise. Such a combination is increasingly viewed as being synergistic in solving complex problems in biomedical research ( 45 , 46 ).…”
Section: Discussionmentioning
confidence: 99%
“…Consequently, there is an opportunity for model‐informed decision making to be based on the totality of clinical data, integrating all relevant clinical PK/PD, efficacy, and safety end points from an FIH trial, and the combined use of pharmacometrics and statistical methods in the early stage of clinical development. This type of model‐informed decision making echoes the advocacy of synergy between pharmacometrics and statistics, 22 and has the potential to provide more comprehensive quantitative support for dose selection, which ultimately could benefit the overall drug development.…”
Section: Figurementioning
confidence: 88%
“…Maximizing Bayesian frameworks for dose optimization will depend on interdisciplinary alliances between pharmacologists and statisticians, 45 and the dynamic exchange of ideas and lessons between scientists in industry and regulatory agencies 5 . The harmonized learnings from these collaborative interactions can further acceptance of the quantitative clinical pharmacology framework and set a precedent for subsequent oncology clinical development programs, ultimately fully realizing the promise of Bayesian methodologies in oncology drug development.…”
Section: Pharmacostatistical Models and Novel Trial Designsmentioning
confidence: 99%